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\section{Conclusion}
\label{sec:conclusion}

In journalism, claims derived from data are important ingredients for
many stories, ranging from politics to sports.  A common analysis for
determining the quality of a claim is to compare it with other claims
of the same form.  Such exploratory analysis can usually be carried
out effectively via visualization.  In this paper, we consider claims
that can be modeled as queries whose results can be represented as 2d
points, and we focus on one common type of visualization---a
combination of 2d scatter plot for outliers and a heatmap for overall
distribution.  We propose an efficient two-phase sampling-based
algorithm that works with any query function.  The algorithm first
executes the query function on a sample of the dataset, and then,
based on the result, further selects additional data to access in
order to produce a final approximate answer.  Experiments show that
our algorithm is efficient and is able to preserve result properties
important to visualization---namely the outliers and the overall
distribution.
